Using data available up to the: 2020-04-14
Note that it takes time for infection to cause symptoms, to get tested for SARS-CoV-2 infection, for a positive test to return and ultimately to enter the case data presented here. In other words, today’s case data are only informative of new infections about two weeks ago. This is reflected in the plots below, which are by date of infection.
Expected daily confirmed cases by country
Figure 1: The results of the latest reproduction number estimates (based on estimated confirmed cases with a date of infection on the 2020-04-04) can be summarised by whether confirmed cases are likely increasing or decreasing. This represents the strength of the evidence that the reproduction number in each region is greater than or less than 1, respectively (see the methods for details). Countries with fewer than 100 confirmed cases reported on a single day are not included in the analysis (light grey) as there is not enough data to reliably estimate the reproduction number.
Summary of latest reproduction number and confirmed case count estimates by date of infection
Figure 1: Confirmed cases with date of infection on the 2020-04-04 and the time-varying estimate of the effective reproduction number (light bar = 90% credible interval; dark bar = the 50% credible interval.). Regions are ordered by the number of expected daily confirmed cases and shaded based on the expected change in daily confirmed cases. The dotted line indicates the target value of 1 for the effective reproduction no. required for control and a single case required for elimination.
Reproduction numbers over time in the six regions expected to have the most new confirmed cases
Figure 2: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates are shown up to the 2020-04-04. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The dotted line indicates the target value of 1 for the effective reproduction no. required for control.
Reported confirmed cases and their estimated date of infection in the six regions expected to have the most new confirmed cases
Figure 3: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates are shown up to the 2020-04-04. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence.
Reproduction numbers over time in all regions
Figure 4: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates are shown up to the 2020-04-04. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The dotted line indicates the target value of 1 for the effective reproduction no. required for control.
Reported confirmed cases and their estimated date of infection in all regions
Figure 5: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates are shown up to the 2020-04-04. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence.
Latest estimates (as of the 2020-04-04)
Table 1: Latest estimates (as of the 2020-04-04) of the number of confirmed cases by date of infection, the effective reproduction number, and the doubling time in each region. The mean and 90% credible interval is shown.| Country/Region | New confirmed cases by infection date | Expected change in daily cases | Effective reproduction no. | Doubling time (days) |
|---|---|---|---|---|
| Algeria | 96 (45 – 138) | Unsure | 0.9 (0.7 – 1.2) | -28 (14 – Inf) |
| Argentina | 121 (69 – 180) | Unsure | 1.1 (0.8 – 1.4) | 59 (8.5 – Inf) |
| Australia | 86 (32 – 133) | Decreasing | 0.7 (0.5 – 0.9) | -11 (24 – Inf) |
| Austria | 253 (170 – 331) | Likely decreasing | 0.8 (0.7 – 1) | -31 (29 – Inf) |
| Azerbaijan | 85 (38 – 128) | Unsure | 1.2 (0.8 – 1.5) | 34 (6.6 – Inf) |
| Bahrain | 84 (45 – 127) | Increasing | 1.4 (1 – 1.9) | 8.8 (4.2 – Inf) |
| Bangladesh | 106 (56 – 145) | Increasing | 1.7 (1.2 – 2.2) | 6.2 (3.7 – 19) |
| Belarus | 363 (285 – 433) | Increasing | 1.5 (1.2 – 1.7) | 8.4 (5.8 – 15) |
| Belgium | 1539 (1392 – 1686) | Increasing | 1.1 (1 – 1.1) | 52 (24 – Inf) |
| Brazil | 1546 (1410 – 1720) | Increasing | 1.1 (1 – 1.2) | 33 (18 – 320) |
| Cameroon | 52 (15 – 89) | Unsure | 0.9 (0.5 – 1.3) | -9.8 (14 – Inf) |
| Canada | 1252 (1100 – 1375) | Unsure | 1 (0.9 – 1.1) | -73 (87 – Inf) |
| Chile | 415 (336 – 496) | Likely increasing | 1.1 (1 – 1.2) | 47 (15 – Inf) |
| China | 99 (54 – 142) | Likely increasing | 1.2 (0.9 – 1.5) | 17 (6.2 – Inf) |
| Colombia | 212 (140 – 302) | Likely increasing | 1.2 (0.9 – 1.5) | 17 (7.1 – Inf) |
| Czechia | 184 (114 – 251) | Likely decreasing | 0.9 (0.7 – 1.1) | -24 (25 – Inf) |
| Denmark | 204 (138 – 267) | Decreasing | 0.8 (0.6 – 1) | -13 (Inf – Inf) |
| Dominican Republic | 213 (148 – 266) | Increasing | 1.3 (1 – 1.5) | 14 (7.2 – 240) |
| Ecuador | 712 (580 – 804) | Increasing | 1.5 (1.3 – 1.7) | 7.8 (5.8 – 12) |
| Egypt | 143 (87 – 193) | Likely increasing | 1.1 (0.9 – 1.4) | 38 (8.9 – Inf) |
| Estonia | 59 (14 – 107) | Unsure | 1.1 (0.6 – 1.7) | -100 (5.7 – Inf) |
| Finland | 143 (78 – 206) | Unsure | 1.1 (0.9 – 1.3) | -58 (13 – Inf) |
| France | 3185 (2978 – 3400) | Decreasing | 0.9 (0.9 – 1) | -47 (Inf – Inf) |
| Germany | 3538 (3320 – 3769) | Decreasing | 0.9 (0.9 – 0.9) | -22 (Inf – Inf) |
| Ghana | 71 (39 – 105) | Increasing | 1.7 (1.1 – 2.2) | 6.1 (3.4 – 30) |
| Greece | 76 (33 – 119) | Unsure | 1.1 (0.7 – 1.4) | 57 (6.7 – Inf) |
| Hungary | 132 (75 – 197) | Increasing | 1.4 (1 – 1.7) | 10 (5 – Inf) |
| India | 852 (738 – 952) | Increasing | 1.3 (1.2 – 1.4) | 17 (11 – 37) |
| Indonesia | 325 (250 – 383) | Increasing | 1.3 (1.1 – 1.5) | 13 (7.8 – 47) |
| Iran | 1796 (1622 – 1950) | Decreasing | 0.9 (0.8 – 0.9) | -18 (Inf – Inf) |
| Iraq | 62 (25 – 100) | Unsure | 1 (0.7 – 1.3) | -50 (8.4 – Inf) |
| Ireland | 809 (707 – 912) | Increasing | 1.3 (1.2 – 1.5) | 11 (8.1 – 18) |
| Israel | 405 (324 – 475) | Decreasing | 0.9 (0.8 – 1) | -21 (420 – Inf) |
| Italy | 4234 (3997 – 4482) | Unsure | 1 (0.9 – 1.1) | 200 (47 – Inf) |
| Japan | 773 (666 – 876) | Increasing | 1.5 (1.3 – 1.7) | 7.7 (5.9 – 11) |
| Kazakhstan | 61 (25 – 93) | Unsure | 1.1 (0.7 – 1.4) | -130 (7.9 – Inf) |
| Kuwait | 115 (61 – 162) | Likely increasing | 1.2 (0.9 – 1.6) | 22 (6.6 – Inf) |
| Lithuania | 61 (19 – 105) | Unsure | 1.2 (0.7 – 1.7) | 25 (4.7 – Inf) |
| Luxembourg | 91 (31 – 144) | Unsure | 1 (0.6 – 1.3) | -53 (8.7 – Inf) |
| Malaysia | 154 (103 – 206) | Unsure | 1 (0.8 – 1.1) | -76 (15 – Inf) |
| Mexico | 388 (311 – 463) | Increasing | 1.2 (1.1 – 1.4) | 18 (9.5 – 120) |
| Moldova | 135 (80 – 192) | Likely increasing | 1.2 (0.9 – 1.4) | 38 (8.4 – Inf) |
| Morocco | 107 (58 – 147) | Unsure | 1.1 (0.8 – 1.4) | 94 (9 – Inf) |
| Netherlands | 1248 (1113 – 1384) | Increasing | 1.1 (1 – 1.1) | 31 (17 – 180) |
| Norway | 110 (59 – 153) | Likely decreasing | 0.8 (0.6 – 1) | -11 (160 – Inf) |
| Pakistan | 269 (204 – 330) | Likely decreasing | 0.9 (0.7 – 1.1) | -21 (94 – Inf) |
| Panama | 229 (164 – 290) | Likely increasing | 1.2 (1 – 1.4) | 22 (9 – Inf) |
| Peru | 818 (710 – 921) | Increasing | 1.3 (1.1 – 1.5) | 11 (7.9 – 21) |
| Philippines | 203 (144 – 257) | Likely decreasing | 0.9 (0.8 – 1) | -73 (18 – Inf) |
| Poland | 366 (294 – 434) | Unsure | 1 (0.9 – 1.2) | -360 (23 – Inf) |
| Portugal | 832 (713 – 939) | Likely increasing | 1.1 (1 – 1.1) | 39 (17 – Inf) |
| Puerto Rico | 80 (42 – 117) | Likely increasing | 1.3 (0.9 – 1.7) | 14 (5.3 – Inf) |
| Qatar | 199 (139 – 246) | Unsure | 1 (0.8 – 1.2) | -67 (20 – Inf) |
| Romania | 383 (311 – 456) | Likely increasing | 1.1 (1 – 1.2) | 40 (14 – Inf) |
| Russia | 1784 (1636 – 1951) | Increasing | 1.4 (1.3 – 1.5) | 9.9 (8 – 13) |
| Saudi Arabia | 378 (295 – 443) | Increasing | 1.4 (1.2 – 1.6) | 11 (6.9 – 22) |
| Serbia | 249 (190 – 313) | Unsure | 1.1 (0.9 – 1.2) | 200 (16 – Inf) |
| Singapore | 230 (163 – 285) | Increasing | 1.5 (1.2 – 1.7) | 8.6 (5.4 – 21) |
| Slovakia | 39 (3 – 73) | Unsure | 1.1 (0.4 – 1.6) | -45 (4.9 – Inf) |
| South Africa | 90 (47 – 125) | Likely increasing | 1.2 (0.8 – 1.6) | 19 (6.4 – Inf) |
| South Korea | 44 (9 – 72) | Likely decreasing | 0.8 (0.5 – 1.1) | -13 (11 – Inf) |
| Spain | 4797 (4499 – 5027) | Decreasing | 0.9 (0.8 – 0.9) | -27 (Inf – Inf) |
| Sweden | 501 (413 – 581) | Unsure | 1 (0.9 – 1.1) | 130 (21 – Inf) |
| Switzerland | 601 (504 – 689) | Decreasing | 0.9 (0.8 – 0.9) | -23 (Inf – Inf) |
| Thailand | 55 (16 – 92) | Likely decreasing | 0.8 (0.5 – 1) | -10 (18 – Inf) |
| Turkey | 4728 (4461 – 4980) | Increasing | 1.2 (1.2 – 1.3) | 19 (15 – 25) |
| Ukraine | 283 (209 – 338) | Increasing | 1.4 (1.1 – 1.6) | 10 (6.3 – 25) |
| United Arab Emirates | 370 (305 – 444) | Increasing | 1.2 (1 – 1.4) | 27 (12 – Inf) |
| United Kingdom | 6076 (5829 – 6408) | Increasing | 1.2 (1.1 – 1.2) | 22 (17 – 30) |
| United States of America | 30907 (30193 – 31525) | Increasing | 1 (1 – 1.1) | 940 (150 – Inf) |
| Uzbekistan | 98 (53 – 146) | Likely increasing | 1.4 (1 – 1.8) | 13 (5.3 – Inf) |